In the process of image formation, there are difficulties associated with rendering certain reverse features on an image output medium. Reverse features are those in which white, near-white, or essentially transparent images, are to be disposed on the output image receiving medium within an area including a dark or color background. Conventional methods for enhancing image quality in produced images tend to lead to a blending of individual opposing edges that wash out a small text font or fine line object image particularly as the size of the image is reduced. Depending on the image formation method employed by an image forming device, and on a dot-per-inch resolution for the formed image, an ability to render and/or print finely-defined features, particularly in reverse printing may be affected. A particular image forming methodology by which such images maybe rendered less perceptible as the width of fine lines or the size of fonts are reduced involves electrostatic and/or xerographic image formation.
In many xerographic image forming systems and/or devices, for example, fill-in artifacts which have been included to enhance crispness often remain perceptible when printing reverse fine features, such as fine lines or small text fonts, in white on a dark or color background. These fill-in artifacts may obliterate the fine lines and/or small text fonts. Such problems associated with printing reverse fine features are increasingly pronounced in circumstances when, for example, high addressability halftones are employed at the edges of adjacent background pixels, and/or when the background color contains an excessive toner amount. Bleed of the fine edge adjustments into the white fine line or small text font areas result in the reverse fine features becoming indistinct or difficult to recognize and/or read. This reduces the sharpness or crispness of the output image. Sharpness is generally an important metric for evaluating image quality. FIGS. 1A-C are demonstrative of this problem. FIG. 1 is an exemplary line of white text on a dark color background. FIG. 2 is an unmodified line of white on a light color background. FIG. 3 is an unmodified set of radiating lines with varying pixel widths. As can be seen, as fine lines become thinner and small text is reduced below a threshold object size, the sharpness of the images decreases, i.e., the visibility of individual features decreases dramatically.
Image forming systems enhance sharpness by various methods including modifying edge pixels of an object to employ high addressability halftone screens, while still employing base dot screens for the non-edge pixels. Such methods can be effective in enhancing sharpness of the formed image in reverse printing lines and text characters when the involved object is white, and of normal-to-large size, and the background is dark or darkly colored. High addressability halftones are applied to the colored edge pixels that belong to the background to enhance this sharpness. However, for small text fonts and fine lines, simple readability becomes a more important attribute than individual object or character sharpness. Conventional solutions often address such problems by disabling the high addressable halftone cells for reverse objects when the objects are below a certain size threshold. This approach leaves white areas more perceptible but these objects may be blurry when the background is light or a lighter color. Other methods involve globally thickening a stroke size for thin reverse lines. However, such methods also tend to thicken the positive or color line.
U.S. Patent Publication No. 2009/0153923, entitled: “Methods And Systems For Rendering And Printing Reverse Fine Features” disclosed a method for calculating a base dilation amount applied to all background colors. However, in this context, a one-size-fits-all solution is not optimal. If a base dilation amount is applied to all background colors for the same fine line, one can observe that dilation does not open up the thin line sufficiently enough in a dark background while opening up the line too much in a light background. Consider, for instance, a thin line located on a dark (100%) to light (0%) sweep. The fill-in effect will not be constant. This non-linearity can also be observed as color halos near edges of small reverse fine-featured objects. For instance, given a document image, such as a PDL page, that has some relatively small white text lines on top of a red box wherein CMYK=(0,255,128,0), if we dilate a small but substantially similar amount for Magenta and Yellow in the rasterized image, a white gap can be observed if the area of Magenta separation gets filled too much. Stated differently, with the same amount of dilation, the white gap in the Magenta separation will be narrower than in the Yellow separation. If we increase the dilation amount for this same small white text line such that the white gap in the Magenta separation is widened sufficient to avoid the fill-in artifact effect, the same amount of dilation may be too much in the Yellow separation.
Accordingly, what is needed in this art are increasingly sophisticated systems and methods which can compensate for fill-in artifact effects and which can account for both object size and background color per color separation to improve image quality in digital document reproduction devices.